Design and implement solutions using Microsoft Copilot Studio, Microsoft 365 Copilot, and Azure OpenAI
Extend Copilot capabilities through custom engineering, including backend APIs and retrieval systems
Build and maintain LLM-powered services that support Copilot extensions and standalone enterprise use cases
Design and implement retrieval-augmented generation (RAG) pipelines, including:
Document ingestion and normalization
Chunking, metadata, and embedding strategies
Indexing using vector and hybrid search approaches
Implement hybrid retrieval strategies (keyword + vector + reranking) for grounded AI outputs
Integrate AI solutions with enterprise systems such as SharePoint, Microsoft Graph, SQL, and internal APIs
Design systems with clear attention to:
Security and data access boundaries
Reliability and failure handling
Performance, latency, and cost efficiency in Azure
Establish evaluation, monitoring, and quality metrics for Copilot and LLM-based systems
Collaborate with client stakeholders to translate business needs into Copilot-first, extensible AI solutions

Requirements

5+ years of experience in software engineering, AI/ML systems, or enterprise platforms
Hands-on experience within the Microsoft Copilot ecosystem
Practical experience with Azure OpenAI Service
Strong Python skills and experience building production APIs (FastAPI, Flask, or similar)
Experience designing and implementing RAG-based systems
Solid understanding of prompt design, context management, and grounding techniques
Experience integrating AI solutions with enterprise data sources
Comfort working in secure, governed enterprise environments

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

PythonFastAPIFlaskRAG-based systemsprompt designcontext managementgrounding techniquesbackend APIsretrieval systemsLLM-powered services

Soft Skills

collaborationcommunicationproblem-solvingattention to detailstakeholder engagement